We present the Radar de Parit\'e, an automated Natural Language Processing (NLP) system that measures the proportion of women and men quoted daily in six Canadian French-language media outlets. We outline the system's architecture and detail the challenges we overcame to address French-specific issues, in particular regarding coreference resolution, a new contribution to the NLP literature on French. We also showcase statistics covering over one year's worth of data (282,512 news articles). Our results highlight the underrepresentation of women in news stories, while also illustrating the application of modern NLP methods to measure gender representation and address societal issues.

本研究介绍了雷达德帕里特（Radar de Parité）系统，一个自动的自然语言处理系统，用来测量六个加拿大的法语媒体每日引用的男女比例。我们详细介绍了该系统的架构，并阐述了我们解决法语特定问题，特别是关于核指代消解的挑战，这对法语的自然语言处理文献做出了新的贡献。我们还展示了超过一年的数据（282,512篇新闻文章）的统计数据。我们的结果突出了新闻报道中女性的代表性低下，同时也说明了现代自然语言处理方法在衡量性别代表性并解决社会问题方面的应用。

Radar de Parité：一种测量法国新闻报道中性别再现的NLP系统